library(readxl)
library(tidyverse)
sep07 <- read.csv("../data/clean_data/npoc_7sep21.csv")%>%
mutate(Day = as.Date("2021-09-07"))
sep08 <- read.csv("../data/clean_data/npoc_8sep21.csv")%>%
mutate(Day = as.Date("2021-09-08"))
sep09 <- read.csv("../data/clean_data/npoc_9sep21.csv")%>%
mutate(Day = as.Date("2021-09-09"))
full = sep07%>%
full_join(sep08)%>%
full_join(sep09)%>%
filter(!grepl("spk|dup",Sample))
Joining, by = c("Sample", "NPOC", "TNb", "Day")
Joining, by = c("Sample", "NPOC", "TNb", "Day")
full$Type = "Unknown"
full$Sample_day <- as.numeric(sub("[a-z]+[0-9]+d","",sub("([a-z](_.+)*$)","",full$Sample)))
full$Rep <- as.numeric(substr(full$Sample,4,4))
full$filt <- sub("[a-z]+[0-9]+[a-z]+[0-9]+","",sub("_.+","",full$Sample))
full$Treatment <- substr(full$Sample,1,2)
full_conc = full
full_conc$Treatment[full_conc$Treatment=="ao"&full_conc$Sample_day<=13]<-"Anoxic"
full_conc$Treatment[full_conc$Treatment=="oa"&full_conc$Sample_day<=13]<-"Oxic"
full_conc$Treatment[full_conc$Treatment=="aa"]<-"Anoxic"
full_conc$Treatment[full_conc$Treatment=="oo"]<-"Oxic"
full_conc$Treatment[full_conc$Treatment=="oa"]<-"Oxic to anoxic"
full_conc$Treatment[full_conc$Treatment=="ao"]<-"Anoxic to oxic"
fer = full_conc
fer$filt[fer$filt=="s"]<-"Filtered"
fer$filt[fer$filt=="t"]<-"Unfiltered"
fer$Status <- "Oxic"
fer$Status[fer$Treatment %in%c("Anoxic to oxic","Anoxic")]<- "Anoxic"
f = fer%>%
filter(!is.na(Treatment))%>%
ggplot(aes(x = Sample_day, y = NPOC, color = Treatment))+
geom_point()+
ylab("NPOC")+
geom_vline(xintercept = 13.5)+
scale_color_manual(values = c("#175676","#D58936","#A44200","#4BA3C3")) +
facet_grid(Status~filt)
library(plotly)
ggplotly(f)
fer%>%
filter(Sample_day == 34,
filt == "Filtered")
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